A quantitative retirement and investment platform for self-directed investors, financial advisors, and institutions — powered by an 11-layer intelligence engine with published methodology and live falsifiability testing. Applications open Q4 2026 (target October 15–31), gated on the methodology white paper and four months of live track record.
Every investor deserves the same analytical depth as a quantitative wealth manager — transparent, testable, and honest about what it doesn’t know.
Build a retirement and investment platform that publishes its methodology, tests itself against random allocation daily, and reports the result either way.
Full lifecycle planning. Live market intelligence. Every assumption visible.
Monday morning, you open Arya. It tells you which account to fund, how much to convert from your IRA to Roth before the tax-bracket window closes, whether to harvest a loss or let it ride, and what to leave alone — with the dollar math behind every recommendation. Then it runs that same logic on a paper portfolio and tracks how it performs against five random-pick portfolios, publishing the result either way.
Built for the self-directed investor who wants institutional-grade analytics. For the financial advisor who wants a quantitative backbone for their practice. For anyone who believes investment decisions should be backed by transparent, testable methodology — not gut feel.
Four steps from “what if” to a plan you can defend to yourself at 3 AM.
You have three accounts, two incomes, a pension that starts at 62, and a nagging feeling that your current plan is built on guesswork. Most tools would lump all that together and give you a single number. Arya models each account separately — because the same $100K in taxable versus Roth has three different after-tax futures and three different optimal strategies.
Per-account balances and allocations. Social Security, pensions, part-time income. Named strategies from portfoliocharts.com (Golden Butterfly, All Seasons, Pinwheel) and NDinomics originals. Market shock scenarios baked in.
Two strategies with identical 30-year returns — but one drops 45% in year 8 while the other drops 18%. Same destination, very different rides. One algorithm might miss it. Six won’t. Your retirement is too important for a single opinion. Compare up to four side by side and see which one you can actually live with.
NDI-Monte Carlo ensemble, Hamiltonian Monte Carlo, Bellman Conformal Inference with mathematically guaranteed coverage, Importance Sampling for tail-risk focus, Kelly CVaR for optimal position sizing, and Drawdown-Aware Efficient Frontier that optimizes for maximum drawdown — the risk that actually keeps you up at night.
Your NVDA is 35% of your portfolio with 18,000% embedded gain. Put cost: $9.5K/yr. Cap-gains tax if you sold: $45K. The math most people never do — Arya does it automatically, per account, per lot, with tax-bracket awareness that updates as your income changes throughout the year. You finally have the same depth as a billionaire’s wealth manager.
Federal + state tax modeling. Roth conversion optimization. RMD projections. Covered-call tax treatment by account type (aggressive in Roth, per-lot in taxable). Event Sequence Intelligence captures multi-ribbon patterns and matches them against historical crises before they fully develop.
Axiom beat 4 of 5 random portfolios this quarter — but not the 5th. We publish that. Most platforms show you backtested returns designed after the fact to look good. Arya runs a live experiment and shows you the raw numbers, including the ones that make us look bad. Because your trust matters more than our pride.
Every Axiom-driven strategy runs alongside five random “dartboard” portfolios in real time. Same rebalance cadence. Same fee assumptions. Same calendar. No survivorship bias. No cherry-picking. If Axiom can’t beat random with statistical significance, we’ll say so publicly.
Your retirement is too important for a single opinion. Each algorithm answers a different question about your financial future. Run all six and compare.
Our calibrated ensemble. Axiom-weighted return distributions, regime-aware volatility, year-by-year tax and withdrawal modeling. The workhorse — 10,000 paths, each one a plausible future.
Physics-inspired sampling that explores the return landscape more efficiently than random walks. Finds the corners of your risk space that other methods miss.
When BCI says “90% of outcomes fall here,” the coverage is provably correct — no assumptions about the shape of returns. Mathematical certainty, not statistical hope.
Oversamples rare catastrophic scenarios. See what happens in the 1% tail — the scenarios Monte Carlo barely touches but your retirement depends on surviving.
Growth-optimal position sizing constrained by Conditional Value at Risk. Answers: “How much can I afford to bet on this allocation without risking ruin?”
Traditional efficient frontier optimizes for variance. Ours optimizes for maximum drawdown — the risk that actually makes people panic-sell at the bottom.
Axiom calibrates hundreds of assets from live global market data on a regular cycle. Multiple intelligence layers feed every simulation, every recommendation, every alert. You see clear answers. This is what powers them.
Multi-ribbon event capture monitors how economic signals unfold in sequence — not in isolation. ESI matches current patterns against 2008, 2020, stagflation episodes. The same leading indicators, in the same order, triggering the same early warnings. Because the market rhymes, and the cost of missing the rhyme is your retirement.
See how events propagate across your portfolio with probability-weighted scenarios. Where others give you a number, Arya gives you a landscape — because the future is a distribution, not a point, and planning for the median while ignoring the tails is how people run out of money.
Anomalous volume spikes, coordinated trading patterns, and artificial momentum are flagged against your actual holdings. You see alerts before the market catches up — because this isn’t a headline. It’s your portfolio.
The same $100K in Roth, Traditional IRA, and Brokerage has three different after-tax values and three different optimal strategies. Arya models each account separately — because lumping them together isn’t simplification, it’s a mistake that costs real money.
Variance is a mathematician’s abstraction. Drawdown is what triggers panic selling and retirement delays. Same math, different objective, radically different portfolios — and a very different experience at 3 AM when the market is down 30%.
What happens to your specific portfolio, with your specific withdrawal rate, in your specific tax bracket, if 2008 repeats? Not generic charts — your dollar amounts, your accounts, your shortfall date. The math most advisors never show you.
Most financial tools are built to impress you. Arya is built to be honest with you.
Every return, every volatility, every correlation comes from Axiom calibration on live data. Nothing is hardcoded. If the data changes, the number changes. Because honesty starts with the inputs.
Federal brackets, state rates, IRMAA thresholds, capital gains tiers, Roth conversion ladders, RMD schedules. Fifty-plus tax variables, modeled per account, per year, per scenario. The math most people pay six figures for.
A 35-year-old saving $2K/month and a 68-year-old drawing $8K/month need different algorithms, not the same chart with a different start date. Your life stage changes the math. We change with it.
We show P10 through P90 because the future is a distribution. The median is the most likely outcome. The P10 is what you plan for. The P90 is what you hope for. All three matter. Pretending otherwise is dangerous.
Every Axiom-driven strategy runs alongside five random “dartboard” portfolios — randomly generated allocations with matched rebalance cadence, matched fees, and the same calendar. No backtesting, no cherry-picking, no survivorship bias. If Axiom can’t beat random with statistical significance over four or more quarters, we publish that result. Most platforms show you a carefully curated past. We run a live experiment and show you whatever comes out — because if we can’t be honest about our own results, why would you trust us with yours?